# hello world
print("Hello world")

Hello world

# ⦁	To calculate area of a circle, square and triangle
# calculate area of circle
r = int(input("Enter circle's radius length: "))
pi = 3.14
circ_area = pi * r * r
print(f"The area of triangle is {circ_area}.")

# calculate area of rectangle
l = int(input("Enter rectangle's length: "))
b = int(input("Enter rectangle's breadth: "))
rect_area = l * b
print(f"The area of rectangle is {rect_area}.")

# calculate area of square
s = int(input("Enter square's side length: "))    
sqt_area = s * s
print(f"The area of square is {sqt_area}.")

# calculate area of triangle
h = int(input("Enter triangle's height length: "))
b = int(input("Enter triangle's breadth length: "))  
tri_area = 0.5 * b * h
print(f"The area of triangle is {tri_area}.")

The area of rectangle is 30.

# ⦁	To find out whether a number is Positive, Zero or Negative
num = float(input("Enter a number: "))
if num > 0:
   print("Positive number")
elif num == 0:
   print("Zero")
else:
   print("Negative number")

# ⦁	To get today’s date and current time
import datetime
 
print(datetime.datetime.now())

2021-10-09 17:46:03.400872

# ⦁	To get the version of python on which you are working
import platform
print(platform.python_version())

3.9.7

# ⦁	To convert kilometers to miles
kilometers = float(input("Enter value (km): "))

miles = kilometers * 0.621371
print('%0.2f kilometers is equal to %0.2f miles' %(kilometers,miles))

25.00 kilometers is equal to 15.53 miles

# ⦁	To convert Celsius to Fahrenheit
tempC = float(input("Enter value (celcius): "))
fahrenheit = (tempC * 1.8) + 32
print('%0.1f degree Celsius is equal to %0.1f degree Fahrenheit' %(tempC,fahrenheit))

32.0 degree Celsius is equal to 89.6 degree Fahrenheit

# ⦁	To find whether a string is palindrome. Ask user to give the input a string
def reverse(s):
    return s[::-1]

UserString = input("Enter the string to check for palindrome")

if(reverse(UserString) == UserString):
    print("Its palindrome")
else:
    print("Not a palindrome")

Not a palindrome

# Write a program to calculate simple interest.
p = float(input("  Principal Amount : "))
r = float(input("  Rate Of Interest : "))
t = float(input(" Time : "))

simple_interest = (p * r * t) / 100

print("\nSimple Interest for Principal Amount %0.2f = %0.2f" %(p, simple_interest))

Simple Interest for Principal Amount 5.00 = 1.25

# ⦁	Write a Python program that accepts an integer (n) and computes the value of n+nn+nnn.
i=int(input("Enter a number:"))
num= (i+ ((i*10)+i) + ((i*100)+(i*10)+i))
print(num)

#or
a = int(input("Input an integer : "))
n1 = int( "%s" % a )
n2 = int( "%s%s" % (a,a) )
n3 = int( "%s%s%s" % (a,a,a) )
print (n1+n2+n3)

615
615

# ⦁	Write a Python program to sum of three given integers. However, if two values are equal sum will be zero.
def sum(x, y, z):
    if x == y or y == z or x==z:
        sum = 0
    else:
        sum = x + y + z
    return sum


print(sum(1, 2, 2))
print(sum(4, 2, 3))

0
9

# ⦁	Write a Python program to convert the distance (in feet) to inches, yards, and miles. Write a Python program to convert all units of time into seconds
ft = int(input("Input distance in feet: "))
inches = ft * 12
yards = ft / 3.0
miles = ft / 5280.0

print(" %i inches." % inches)
print(" %.2f yards." % yards)
print(" %.2f miles." % miles)

 60 inches.
 1.67 yards.
 0.00 miles.

# )Write a Python program to construct the following pattern, using a nested for loop.
# *

# * * 

# * * * 

# * * * * 

# * * * * * 

# * * * * 

# * * * 

# * * 

# *

n=5
for i in range(n):
    for j in range(i):
        print ('* ', end="")
    print('')

for i in range(n,0,-1):
    for j in range(i):
        print('* ', end="")
    print('')

* 
* * 
* * * 
* * * * 
* * * * * 
* * * * 
* * * 
* * 
* 

#  Find numbers which are divisible by 7 and multiple of 5 between a range Find numbers which are divisible by 7 and multiple of 5 between a range
nl=[]
for x in range(1500, 2701):
    if (x%7==0) and (x%5==0):
        print(x)

1505
1540
1575
1610
1645
1680
1715
1750
1785
1820
1855
1890
1925
1960
1995
2030
2065
2100
2135
2170
2205
2240
2275
2310
2345
2380
2415
2450
2485
2520
2555
2590
2625
2660
2695

# Write a Python program to count the number of even and odd numbers from a series of numbers. Sample numbers : 
# numbers = (1, 2, 3, 4, 5, 6, 7, 8, 9) 
# Expected Output :
# Number of even numbers : 4
# Number of odd numbers : 5
numbers = (1, 2, 3, 4, 5, 6, 7, 8, 9) 
odd = 0
even = 0
for x in numbers:
        if not x % 2:
    	     even+=1
        else:
    	     odd+=1
print("Number of even numbers :",even)
print("Number of odd numbers :",odd)

Number of even numbers : 4
Number of odd numbers : 5

# Write a Python program that prints all the numbers from 0 to 6 except 3 and 6.
# Note : Use 'continue' statement.
for x in range(6):
    if (x == 3 or x==6):
        continue
    print(x,end=' ')
print("\n")

0 1 2 4 5 

# Write a Python program to get the Fibonacci series between 0 to 50. 
x,y=0,1

while y<50:
    print(y)
    x,y = y,x+y
	

1
1
2
3
5
8
13
21
34

# Write a Python program to print alphabet pattern 'A'.
result_str="";    
for row in range(0,7):    
    for column in range(0,7):     
        if (((column == 1 or column == 5) and row != 0) or ((row == 0 or row == 3) and (column > 1 and column < 5))):    
            result_str=result_str+"*"    
        else:      
            result_str=result_str+" "    
    result_str=result_str+"\n"    
print(result_str)

  ***  
 *   * 
 *   * 
 ***** 
 *   * 
 *   * 
 *   * 

# Write a program to check whether a number is Prime number or not.
num = int(input("Enter a number : "))
if num > 1:

    for i in range(2, int(num/2)+1):
        if (num % i) == 0:
            print(num, "is not a prime number")
            break
    else:
        print(num, "is a prime number")
 
else:
    print(num, "is not a prime number")

25 is not a prime number

# factorial
def factorial(n):
    return 1 if (n==1 or n==0) else n * factorial(n - 1)
 

num = int(input("Enter a number: "))
print ("Factorial of",num,"is",factorial(num))

Factorial of 20 is 2432902008176640000

# Multiplication table (from 1 to 10) in Python

num = int(input("Enter a number : "))

for i in range(1, 11):
   print(num, 'x', i, '=', num*i)

25 x 1 = 25
25 x 2 = 50
25 x 3 = 75
25 x 4 = 100
25 x 5 = 125
25 x 6 = 150
25 x 7 = 175
25 x 8 = 200
25 x 9 = 225
25 x 10 = 250

#Armstrong Number
lower = int(input("Enter the lower limit"))
upper = int(input("Enter the upper limit"))

for num in range(lower, upper + 1):
#    print(str(num))
   order = len(str(num))
    
   sum = 0

   temp = num
   while temp > 0:
       digit = temp % 10
       sum += digit ** order
    #    print(temp / 10)
       temp = temp // 10

   if num == sum:
       print(num)

# Python Program to find the factors of a number

def factors(n):
   print("The factors of",n,"are:")
   for i in range(1, n + 1):
       if n % i == 0:
           print(i)

num = int(input("Enter a number : "))

factors(num)

The factors of 25 are:
1
5
25

# HCF and LCM
def get_gcd(a,b):
    gcd = 1
    for i in range(1,a+1):
        if a%i==0 and b%i==0:
           gcd = i
    return gcd


first = int(input('Enter first number: '))
second = int(input('Enter second number: '))
gcd = get_gcd(first, second)
print('HCF or GCD of %d and %d is %d' %(first, second,gcd ))


lcm = first * second / gcd
print('LCM of %d and %d is %d' %(first, second, lcm))

HCF or GCD of 25 and 63 is 1
LCM of 25 and 63 is 1575

# ⦁	Write a Python program to sum all the items in a list
def sum_list(items):
    sum_numbers = 0
    for x in items:
        sum_numbers += x
    return sum_numbers
print(sum_list([5,2,-3]))

4

# ⦁	Write a Python program to get the largest and smallest number from a list.\
numList = [4,56,65,654,654,464,22,3]
print("\nThe Smallest Element in this List is: ", min(numList))
print("The Largest Element in this List is: ", max(numList))

# or
numList.sort()

print("\nThe Smallest Element in this List is : ", numList[0])
print("The Largest Element in this List is : ", numList[- 1])

The Smallest Element in this List is:  3
The Largest Element in this List is:  654

The Smallest Element in this List is :  3
The Largest Element in this List is :  654

# ⦁	Write a Python program to check a list is empty or not.
l = []
if not l:
  print("List is empty")

# or



if len(l) == 0:
    print("List is empty")
else:
    print("List is not empty")
 

List is empty
List is empty

# ⦁	Write a Python program to clone or copy a list.
listo = [11, 23, 45, 24, 5]
listn = list(listo)
print(listo)
print(listn)

[11, 23, 45, 24, 5]
[11, 23, 45, 24, 5]

# ⦁	Write a Python program to print a specified list after removing the 0th, 4th and 5th elements. 
color = ['Red', 'Green', 'White', 'Black', 'Pink', 'Yellow']
color = [x for (i,x) in enumerate(color) if i not in (0,4,5)]
print(color)

['Green', 'White', 'Black']

# ⦁	Write a Python program access the index of a list.
l = [3, 45, 85, 81, 113]
for num, val in enumerate(l):
    print(num, val)

0 3
1 45
2 85
3 81
4 113

# ⦁	Write a Python program to append a list to the second list. 
list1 = [1, 2, 3, 0]
list2 = ['Red', 'Green', 'Black']
final_list = list1 + list2
print(final_list)

[1, 2, 3, 0, 'Red', 'Green', 'Black']

# ⦁	Write a Python program to select an item randomly from a list. 
import random
color_list = ['Red', 'Blue', 'Green', 'White', 'Black']
print(random.choice(color_list))

White

# ⦁	Write a Python program to get unique values from a list. 
nList = [10, 20, 30, 40, 20, 50, 60, 40]
uList = []
     
for x in nList:
    if x not in uList:
            uList.append(x)
print(uList)

# or

print("Original List : ",nList)
my_set = set(nList)
print(my_set)
my_new_list = list(my_set)
print("List of unique numbers : ",my_new_list)
     
   

[10, 20, 30, 40, 50, 60]
Original List :  [10, 20, 30, 40, 20, 50, 60, 40]
{40, 10, 50, 20, 60, 30}
List of unique numbers :  [40, 10, 50, 20, 60, 30]

# ⦁	Write a Python program to get the second largest and second smallest 
numList = [4,56,65,654,654,464,22,3]
numList.sort()
print("Second Smallest : %i"  %numList[1])
print("Second Largest : %i" %numList[-2])

Second Smallest : 4
Second Largest : 654

# ⦁	Write a Python program to remove duplicates from a list.
nList = [10, 20, 30, 40, 20, 50, 60, 40]
print("Original List : ",nList)
my_set = set(nList)
# print(my_set)
nList = list(my_set)
print("New list : ",nList)

Original List :  [10, 20, 30, 40, 20, 50, 60, 40]
New list :  [40, 10, 50, 20, 60, 30]

# count characters 
test_str = input("Enter a string : ")
  
# using naive method to get count 
# of each element in string 
all_freq = {}
  
for i in test_str:
    if i in all_freq:
        all_freq[i] += 1
    else:
        all_freq[i] = 1
  
# printing result 
print ("Count of all characters in given string is :\n "
                                        +  str(all_freq))

Count of all characters in given string is :
 {'d': 1, 'e': 2, 'p': 1, 'a': 1, 'k': 1}

# ⦁	Write a Python program to get a single string from two given strings, separated by a space and swap the first two characters of each string.
def swapFirstTwoCharacters(a, b):
  str1 = b[:2] + a[2:]
  str2 = a[:2] + b[2:]

  return str1 + ' ' + str2

str1 = input("Enter string 1 : ")

str2 = input("Enter string 2 : ")
print(swapFirstTwoCharacters(str1, str2))

paepak dewade

# ⦁	Write a Python program to add 'ing' at the end of a given string (length should be at least 3). If the given string already ends with 'ing' then add 'ly' instead. If the string length of the given string is less than 3, leave it unchanged.
def add_suffix(str1):
  length = len(str1)

  if length > 2:
    if str1[-3:] == 'ing':
      str1 += 'ly'
    else:
      str1 += 'ing'

  return str1

Str = input("Enter a string : ")
print(add_suffix(Str))

helloingly

# ⦁	Write a Python program to find the first appearance of the substring 'not' and 'poor' from a given string, if 'not' follows the 'poor', replace the whole 'not'...'poor' substring with 'good'. Return the resultin
def not_poor(str1):
  snot = str1.find('not')
  spoor = str1.find('poor')
  

  if spoor > snot and snot>0 and spoor>0:
    str1 = str1.replace(str1[snot:(spoor+4)], 'good')
    return str1
  return str1
  
Str = input("Enter a String : ")
print(not_poor(Str))

its good

# tuple 
my_tuple = ("red", "blue", "green")
print(my_tuple)

('red', 'blue', 'green')

#Create a tuple with different data types
tuple1 = ("tuple", False, 3.2, 1)
print(tuple1)

('tuple', False, 3.2, 1)

#Create a tuple with numbers
tuplex = 5, 10, 15, 20, 25
print(tuplex[0])

5

# add item in a tuple
tuple1 = (4, 6, 2, 8, 3, 1) 
print(tuple1)

tuple1 = tuple1 + (66,)
print(tuple1)

tuplex = tuplex[:5] + (15, 20, 25) + tuplex[:5]
print(tuplex)

listx = list(tuplex) 

listx.append(30)
tuplex = tuple(listx)
print(tuplex)

(4, 6, 2, 8, 3, 1)
(4, 6, 2, 8, 3, 1, 66)
(4, 6, 2, 8, 3, 15, 20, 25, 4, 6, 2, 8, 3)
(4, 6, 2, 8, 3, 15, 20, 25, 4, 6, 2, 8, 3, 30)

# ⦁	Write a Python program to get the 4th element and 4th element from last of a tuple.
tuple1 = (4, 6, 2, 8, 3, 1)
print(tuple1[3])
print(tuple1[-4])

8
2

# ⦁	Write a Python program to check whether an element exists within a tuple.
tuple1 = (4, 6, 2, 8, 3, 1)
print(5 in tuple1)
print(4 in tuple1)

False
True

# ⦁	Write a Python program to convert a list to a tuple.
tuple1 = (4, 6, 2, 8, 3, 1)
print(list(tuple1))

[4, 6, 2, 8, 3, 1]

# ⦁	Write a Python program to slice a tuple.

tuple1 = (4, 6, 2, 8, 3, 1)
tuple2 = tuple1[3:5]
print(tuple2)
tuple3 = tuple1[:4]
print(tuple3)

(8, 3)
(4, 6, 2, 8)

# ⦁	Write a Python program to find the index of an item of a tuple.
tuple1 = (4, 6, 2, 8, 3, 1)
print(tuple1.index(3)) 

4

# ⦁	Write a Python program to find the length of a tuple.
tuple1 = (4, 6, 2, 8, 3, 1)
print(len(tuple1))

6

# ⦁	Write a Python program to sort a tuple by its float element
price = [('item1', '12.20'), ('item2', '15.10'), ('item3', '24.5')]
print( sorted(price, key=lambda x: float(x[1]), reverse=True))

[('item3', '24.5'), ('item2', '15.10'), ('item1', '12.20')]

# ⦁	Write a Python script to sort (ascending and descending) a dictionary by value.
import operator
d = {1: 2, 3: 4, 4: 3, 2: 1, 0: 0}
print('Original dictionary : ',d)
sorted_d = sorted(d.items(), key=operator.itemgetter(1))
print('Dictionary in ascending order by value : ',sorted_d)
sorted_d = dict( sorted(d.items(), key=operator.itemgetter(1),reverse=True))
print('Dictionary in descending order by value : ',sorted_d)

Original dictionary :  {1: 2, 3: 4, 4: 3, 2: 1, 0: 0}
Dictionary in ascending order by value :  [(0, 0), (2, 1), (1, 2), (4, 3), (3, 4)]
Dictionary in descending order by value :  {3: 4, 4: 3, 1: 2, 2: 1, 0: 0}

# ⦁	Write a Python script to add a key to a dictionary
d = {0:10, 1:20}
print(d)
d.update({2:30})
print(d)

{0: 10, 1: 20}
{0: 10, 1: 20, 2: 30}

# concatenate dictionaries 
dic1={1:10, 2:20}
dic2={3:30, 4:40}
dic3={5:50,6:60}
dic4 = {}
for d in (dic1, dic2, dic3): dic4.update(d)
print(dic4)

{1: 10, 2: 20, 3: 30, 4: 40, 5: 50, 6: 60}

# check if key present
def checkKey(dict, key):
      
    if key in dict.keys():
        print("\"" + key + "\"" +" Present, ", end =" ")
        print("value =", dict[key])
    else:
        print("\"" +key + "\"" +" Not present")
  
dict = {'a': 100, 'b':200, 'c':300}
  
key = 'b'
checkKey(dict, key)
  
key = 'w'
checkKey(dict, key)

"b" Present,  value = 200
"w" Not present

# ⦁	Write a Python program to iterate over dictionaries using for loops. 

d = {'Red': 1, 'Green': 2, 'Blue': 3} 
for color_key, value in d.items():
     print(color_key, " : ", d[color_key])

Red  :  1
Green  :  2
Blue  :  3

# ⦁	Write a Python script to generate and print a dictionary that contains a number (between 1 and n) in the form (x, x*x). 
n=int(input("Input a number "))
d = {}

for x in range(1,n+1):
    d[x]=x*x

print(d) 

{1: 1, 2: 4, 3: 9, 4: 16, 5: 25, 6: 36}

# ⦁	Write a Python script to print a dictionary where the keys are numbers between 1 and 15 (both included) and the values are square of keys.
d={}
for x in range(1,16):
    d[x]=x**2
print(d)  

{1: 1, 2: 4, 3: 9, 4: 16, 5: 25, 6: 36, 7: 49, 8: 64, 9: 81, 10: 100, 11: 121, 12: 144, 13: 169, 14: 196, 15: 225}

# ⦁	Write a Python script to merge two Python dictionaries.
d1 = {'a': 100, 'b': 200}
d2 = {'x': 300, 'y': 200}
d = d1.copy()
d.update(d2)
print(d)

{'a': 100, 'b': 200, 'x': 300, 'y': 200}

# Write a Python program to sum all the items in a dictionary.
my_dict = {'data1':100,'data2':554,'data3':-247}
print(sum(my_dict.values()))

# or

def returnSum(myDict):
     
    list = []
    for i in myDict:
        list.append(myDict[i])
    final = sum(list)
     
    return final
 
dict = {'a': 100, 'b':200, 'c':300}
print("Sum :", returnSum(dict))

407
Sum : 600

# remove a key
myDict = {'a':1,'b':2,'c':3,'d':4}
print(myDict)
if 'a' in myDict: 
    del myDict['a']
print(myDict)

{'a': 1, 'b': 2, 'c': 3, 'd': 4}
{'b': 2, 'c': 3, 'd': 4}

# ⦁	Write a Python program to get the maximum and minimum value in a dictionary.
my_dict = {'x':500, 'y':5874, 'z': 560}

key_max = max(my_dict.keys(), key=(lambda k: my_dict[k]))
key_min = min(my_dict.keys(), key=(lambda k: my_dict[k]))

print('Maximum Value: ',my_dict[key_max])
print('Minimum Value: ',my_dict[key_min])

Maximum Value:  5874
Minimum Value:  500

# ⦁	Write a Python program to combine two dictionary adding values for common keys. 
dict1 = {'a': 12, 'for': 25, 'c': 9}
dict2 = {'a': 100, 'd': 200, 'c': 300}
  
for key in dict2:
    if key in dict1:
        dict2[key] = dict2[key] + dict1[key]
    else:
        pass
          
print(dict2)

{'a': 112, 'd': 200, 'c': 309}

# ⦁	Write a Python program to print all unique values in a dictionary.  
L = [{"V":"S001"}, {"V": "S002"}, {"VI": "S001"}, {"VI": "S005"}, {"VII":"S005"}, {"V":"S009"},{"VIII":"S007"}]
print("Original List: ",L)
uniqueValues = set( val for dic in L for val in dic.values())
print("Unique Values: ",uniqueValues)

Original List:  [{'V': 'S001'}, {'V': 'S002'}, {'VI': 'S001'}, {'VI': 'S005'}, {'VII': 'S005'}, {'V': 'S009'}, {'VIII': 'S007'}]
Unique Values:  {'S007', 'S009', 'S001', 'S005', 'S002'}

# ⦁	Write a Python program to get the top three items in a shop. 
from heapq import nlargest
from operator import itemgetter
items = {'item1': 45.50, 'item2':35, 'item3': 41.30, 'item4':55, 'item5': 24}
for name, value in nlargest(3, items.items(), key=itemgetter(1)):
    print(name, value)

item4 55
item1 45.5
item3 41.3

# ⦁	Write a Python program to create a set.
my_set = {1, 2, 3}
print(my_set)

# set of mixed datatypes
my_set = {1.0, "Hello", (1, 2, 3)}
print(my_set)

{1, 2, 3}
{1.0, (1, 2, 3), 'Hello'}

# ⦁	Write a Python program to iterate over sets.
my_set = {1.0, "Hello", (1, 2, 3)}
 
# Iterating using for loop
for val in my_set:
    print(val)

1.0
(1, 2, 3)
Hello

# ⦁	Write a Python program to add member(s) in a set.
my_set = {1.0, "Hello", (1, 2, 3)}
my_set.add(11)
print(my_set)
my_set.add("ABC")
print(my_set)

{11, 1.0, (1, 2, 3), 'Hello'}
{'ABC', 1.0, 11, (1, 2, 3), 'Hello'}

# ⦁	Write a Python program to remove item(s) from set 
my_set = {1.0, "Hello", (1, 2, 3)}
my_set.add(11)
print(my_set)
my_set.add("ABC")
print(my_set)
my_set.remove("ABC")
print(my_set)

{11, 1.0, (1, 2, 3), 'Hello'}
{'ABC', 1.0, 11, (1, 2, 3), 'Hello'}
{1.0, 11, (1, 2, 3), 'Hello'}

# ⦁	Write a Python program to remove an item from a set if it is present in the set.
my_set = {1.0, "Hello", (1, 2, 3)}
my_set.add(11)
print(my_set)
my_set.add("ABC")
print(my_set)

if "ABC" in my_set:
    my_set.remove("ABC")
    
print(my_set)

{11, 1.0, (1, 2, 3), 'Hello'}
{'ABC', 1.0, 11, (1, 2, 3), 'Hello'}
{1.0, 11, (1, 2, 3), 'Hello'}

# ⦁	Write a Python program to create an intersection of sets. 
setx = {1, 2, 3, "Hello"}
sety = {1.0, "Hello", (1,2,3)}
print("Original set elements:")
print(setx)
print(sety)
print("\nIntersection of two said sets:")
result = setx.intersection(sety)
print(result)

Original set elements:
{1, 2, 3, 'Hello'}
{1.0, (1, 2, 3), 'Hello'}

Intersection of two said sets:
{1.0, 'Hello'}

# ⦁	Write a Python program to create a union of sets.
setx = {1, 2, 3, "Hello"}
sety = {1.0, "Hello", (1,2,3)}
print("Original set elements:")
print(setx)
print(sety)
print("\nIntersection of two said sets:")
result = setx.union(sety)
print(result)

Original set elements:
{1, 2, 3, 'Hello'}
{1.0, (1, 2, 3), 'Hello'}

Intersection of two said sets:
{1, 2, 3, (1, 2, 3), 'Hello'}

# ⦁	Write a Python program to create set difference.
setx = {1, 2, 3, "Hello"}
sety = {1.0, "Hello", (1,2,3)}
print("Original set elements:")
print(setx)
print(sety)
print("\ndifference of two said sets: first x-y then y-x")
result = setx.difference(sety)
print(result)

result = sety.difference(setx)
print(result)

Original set elements:
{1, 2, 3, 'Hello'}
{1.0, (1, 2, 3), 'Hello'}

difference of two said sets: first x-y then y-x
{2, 3}
{(1, 2, 3)}

# ⦁	Write a Python program to create a symmetric difference.\
setx = {1, 2, 3, "Hello"}
sety = {1.0, "Hello", (1,2,3)}
print("Original set elements:")
print(setx)
print(sety)
print("\ndifference of two said sets: first x-y then y-x")
result = setx.symmetric_difference(sety)
print(result)

result = sety.symmetric_difference(setx)
print(result)

Original set elements:
{1, 2, 3, 'Hello'}
{1.0, (1, 2, 3), 'Hello'}

difference of two said sets: first x-y then y-x
{2, 3, (1, 2, 3)}
{2, 3, (1, 2, 3)}

# ⦁	Write a Python program to issubset and issuperset.
A = {1, 2, 3, 4, 5}
B = {1, 2, 3}
C = {1, 2, 3}

print(A.issuperset(B))
print(B.issuperset(A))
print(B.issubset(A))
print(C.issuperset(B))

True
False
True
True

# ⦁	Write a Python program to create a shallow copy of sets.
my_set = {1, 2, 3}
my_set2 = {1.0, "Hello", (1, 2, 3)}
set3 = my_set.copy()
print(set3)

{1, 2, 3}

# ⦁	Write a Python program to clear a set.
my_set = {1.0, "Hello", (1, 2, 3)}
print(my_set)
my_set.clear()
print(my_set)

{1.0, (1, 2, 3), 'Hello'}
set()

#write a Python function to find the Max of three numbers.
def max_of_two( x, y ):
    if x > y:
        return x
    return y
def max_of_three( x, y, z ):
    return max_of_two( x, max_of_two( y, z ) )
print(max_of_three(5, 7, -9))

7

#Write a Python function to sum all the numbers in a list. Sample List : (8, 2, 3, 0, 7)
#Expected Output : 20
def sum(numbers):
    total = 0
    for x in numbers:
        total += x
    return total
print(sum((8, 2, 3, 0, 7)))

20

#Write a Python function to multiply all the numbers in a list. Sample List : (8, 2, 3, -1, 7)
#Expected Output : -336
def multiply(numbers):  
    total = 1
    for x in numbers:
        total *= x  
    return total  
print(multiply((8, 2, 3, -1, 7)))

-336

#Write a Python function that accepts a string and calculate the number of upper case letters and lower case letters. Go to the editor
#Sample String : 'The quick Brow Fox'
#Expected Output :
#No. of Upper case characters : 3
#No. of Lower case Characters : 12
def string_test(s):
    d={"UPPER_CASE":0, "LOWER_CASE":0}
    for c in s:
        if c.isupper():
           d["UPPER_CASE"]+=1
        elif c.islower():
           d["LOWER_CASE"]+=1
        else:
           pass
    print ("Original String : ", s)
    print ("No. of Upper case characters : ", d["UPPER_CASE"])
    print ("No. of Lower case Characters : ", d["LOWER_CASE"])

string_test('The quick Brown Fox')

Original String :  The quick Brown Fox
No. of Upper case characters :  3
No. of Lower case Characters :  13

#Write a Python function that checks whether a passed string is palindrome or not.
def isPalindrome(UserString):
    def reverse(s):
        return s[::-1]

    if(reverse(UserString) == UserString):
        print("Its palindrome")
    else:
        print("Not a palindrome")

UserString = input("Enter the string to check for palindrome")
isPalindrome(UserString)

Its palindrome

#Write a Python function that prints out the first n rows of Pascal's triangle.
def pascal_triangle(n):
   trow = [1]
   y = [0]
   for x in range(max(n,0)):
      print(trow)
      trow=[l+r for l,r in zip(trow+y, y+trow)]
   return n>=1
pascal_triangle(6) 

[1]
[1, 1]
[1, 2, 1]
[1, 3, 3, 1]
[1, 4, 6, 4, 1]
[1, 5, 10, 10, 5, 1]

True

#Write a Python program that accepts a hyphen-separated sequence of words as input and prints the words in a hyphen-separated sequence after sorting them alphabetically. 
#Sample Items : green-red-yellow-black-white. 
#Expected Result : black-green-red-white-yellow
items=[n for n in input().split('-')]
items.sort()
print('-'.join(items))

black-green-red-white-yellow

#Write a Python function to create and print a list where the values are square of numbers between 1 and 30 (both included).
def printValues():
	l = list()
	for i in range(1,21):
		l.append(i**2)
	print(l)
		
printValues()

[1, 4, 9, 16, 25, 36, 49, 64, 81, 100, 121, 144, 169, 196, 225, 256, 289, 324, 361, 400]

#Write a Python program to make a chain of function decorators (bold, italic, underline etc.) in Python
def make_bold(fn):
    def wrapped():
        return "<b>" + fn() + "</b>"
    return wrapped

def make_italic(fn):
    def wrapped():
        return "<i>" + fn() + "</i>"
    return wrapped

def make_underline(fn):
    def wrapped():
        return "<u>" + fn() + "</u>"
    return wrapped
@make_bold
@make_italic
@make_underline
def hello():
    return "hello world"
print(hello()) 

<b><i><u>hello world</u></i></b>

# Write a NumPy program to test whether any of the elements of a given array is non-zero.
import numpy as np
x = np.array([1, 0, 0, 0])
print(np.any(x))
x = np.array([0, 0, 0, 0])
print(np.any(x))

True
False

#Write a NumPy program to calculate the difference between the maximum and the minimum values of a given array along the second axis.
#Expected Output:Original array:[[ 0 1 2 3 4 5] [ 6 7 8 9 10 11]]
#Difference between the maximum and the minimum values of the said array:[5 5]
import numpy as np
x = np.arange(12).reshape((2, 6))
print("\nOriginal array:")
print(x)
r1 = np.ptp(x, 1)
r2 = np.amax(x, 1) - np.amin(x, 1)
assert np.allclose(r1, r2)
print("\nDifference between the maximum and the minimum values of the array:")
print(r1)

Original array:
[[ 0  1  2  3  4  5]
 [ 6  7  8  9 10 11]]

Difference between the maximum and the minimum values of the array:
[5 5]

#Write a NumPy program to compute the 80th percentile for all elements in a given array along the second axis.
#Expected Output:
#Original array:[1.0, 2.0, 3.0, 4.0]
#Largest integer smaller or equal to the division of the inputs:
# [ 0. 1. 2. 2.]
import numpy as np
x = [1., 2., 3., 4.]
print("Original array:")
print(x)
print("Largest integer smaller or equal to the division of the inputs:")
print(np.floor_divide(x, 1.5))

Original array:
[1.0, 2.0, 3.0, 4.0]
Largest integer smaller or equal to the division of the inputs:
[0. 1. 2. 2.]

#Write a NumPy program to compute the median of flattened given array. 
# Note: First array elements raised to powers from second array
#Expected Output:Original array:[[ 0 1 2 3 4 5][ 6 7 8 9 10 11]]
#Median of said array:5.5
import numpy as np
x = np.arange(12).reshape((2, 6))
print("\nOriginal array:")
print(x)
r1 =  np.median(x)
print("\nMedian of said array:")
print(r1)

Original array:
[[ 0  1  2  3  4  5]
 [ 6  7  8  9 10 11]]

Median of said array:
5.5

#Write a NumPy program to compute the mean, standard deviation, and variance of a given array along the second axis.
#Sample output:Original array:[0 1 2 3 4 5]
#Mean: 2.5
# std: 1
# variance: 2.9166666666666665
import numpy as np
x = np.arange(6)
print("\nOriginal array:")
print(x)
r1 = np.mean(x)
r2 = np.average(x)
assert np.allclose(r1, r2)
print("\nMean: ", r1)
r1 = np.std(x)
r2 = np.sqrt(np.mean((x - np.mean(x)) ** 2 ))
assert np.allclose(r1, r2)
print("\nstd: ", 1)
r1= np.var(x)
r2 = np.mean((x - np.mean(x)) ** 2 )
assert np.allclose(r1, r2)
print("\nvariance: ", r1)

Original array:
[0 1 2 3 4 5]

Mean:  2.5

std:  1

variance:  2.9166666666666665

#Write a NumPy program to compute the weighted average of a given array.
#Sample Output:Original array:[0 1 2 3 4]
#Weighted average of the said array:2.6666666666666665
import numpy as np
x = np.arange(5)
print("\nOriginal array:")
print(x)
weights = np.arange(1, 6)
r1 = np.average(x, weights=weights)
r2 = (x*(weights/weights.sum())).sum()
assert np.allclose(r1, r2)
print("\nWeighted average of the said array:")
print(r1)

Original array:
[0 1 2 3 4]

Weighted average of the said array:
2.6666666666666665

#Write a NumPy program to compute the covariance matrix of two given arrays.
#Sample Output:Original array1:[0 1 2] Original array1:[2 1 0]
#Covariance matrix of the said arrays:[[ 1. -1.] [-1. 1.]]
import numpy as np
x = np.array([0, 1, 2])
y = np.array([2, 1, 0])
print("\nOriginal array1:")
print(x)
print("\nOriginal array1:")
print(y)
print("\nCovariance matrix of the said arrays:\n",np.cov(x, y))

Original array1:
[0 1 2]

Original array1:
[2 1 0]

Covariance matrix of the said arrays:
 [[ 1. -1.]
 [-1.  1.]]

# Write a NumPy program to compute cross-correlation of two given arrays.
#Sample Output:Original array1:[0 1 3] Original array1:[2 4 5]
#Cross-correlation of the said arrays:[[2.33333333 2.16666667] [2.16666667 2.33333333]]
import numpy as np
x = np.array([0, 1, 3])
y = np.array([2, 4, 5])
print("\nOriginal array1:")
print(x)
print("\nOriginal array1:")
print(y)
print("\nCross-correlation of the said arrays:\n",np.cov(x, y))

Original array1:
[0 1 3]

Original array1:
[2 4 5]

Cross-correlation of the said arrays:
 [[2.33333333 2.16666667]
 [2.16666667 2.33333333]]

#Write a NumPy program to compute pearson product-moment correlation coefficients of two given arrays.
#Sample Output:Original array1:[0 1 3] Original array1:[2 4 5]
#Pearson product-moment correlation coefficients of the said arrays:[[1. 0.92857143]
# [0.92857143 1. ]]
import numpy as np
x = np.array([0, 1, 3])
y = np.array([2, 4, 5])
print("\nOriginal array1:")
print(x)
print("\nOriginal array1:")
print(y)
print("\nPearson product-moment correlation coefficients of the said arrays:\n",np.corrcoef(x, y))

Original array1:
[0 1 3]

Original array1:
[2 4 5]

Pearson product-moment correlation coefficients of the said arrays:
 [[1.         0.92857143]
 [0.92857143 1.        ]]

# Write a NumPy program to create an element-wise comparison (greater, greater_equal, less and less_equal) of two given arrays. 
import numpy as np
x = np.array([3, 5])
y = np.array([2, 5])
print("Original numbers:")
print(x)
print(y)
print("Comparison - greater")
print(np.greater(x, y))
print("Comparison - greater_equal")
print(np.greater_equal(x, y))
print("Comparison - less")
print(np.less(x, y))
print("Comparison - less_equal")
print(np.less_equal(x, y))

Original numbers:
[3 5]
[2 5]
Comparison - greater
[ True False]
Comparison - greater_equal
[ True  True]
Comparison - less
[False False]
Comparison - less_equal
[False  True]

# Write a NumPy program to test whether two arrays are element-wise equal within a tolerance.
import numpy as np
print("Test if two arrays are element-wise equal within a tolerance:")
print(np.allclose([1e10,1e-7], [1.00001e10,1e-8]))
print(np.allclose([1e10,1e-8], [1.00001e10,1e-9]))
print(np.allclose([1e10,1e-8], [1.0001e10,1e-9]))
print(np.allclose([1.0, np.nan], [1.0, np.nan]))
print(np.allclose([1.0, np.nan], [1.0, np.nan], equal_nan=True))

Test if two arrays are element-wise equal within a tolerance:
False
True
False
False
True

# Write a NumPy program to test whether none of the elements of a given array is zero.
import numpy as np
x = np.array([1, 2, 3, 4])
print(np.all(x))


x = np.array([0, 1, 2, 3])
print(np.all(x))

True
False

# Write a NumPy program to create an array with the values 1, 7, 13, 105 and determine the size of the memory occupied by the array. 
import numpy as np
X = np.array([1, 7, 13, 105])
print("Original array:")
print(X)
print("Size of the memory occupied by the said array:")
print("%d bytes" % (X.size * X.itemsize))

Original array:
[  1   7  13 105]
Size of the memory occupied by the said array:
16 bytes

# Write a NumPy program to create an array of 10 zeros,10 ones, 10 fives.
import numpy as np
array=np.zeros(10)
print("An array of 10 zeros:")
print(array)
array=np.ones(10)
print("An array of 10 ones:")
print(array)
array=np.ones(10)*5
print("An array of 10 fives:")
print(array)

An array of 10 zeros:
[0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]
An array of 10 ones:
[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
An array of 10 fives:
[5. 5. 5. 5. 5. 5. 5. 5. 5. 5.]

# Write a NumPy program to test element-wise for positive or negative infinity.
import numpy as np, math
a = np.array([1, 0,math.inf, -math.inf, float('inf'), float('-inf')])
print(np.isinf(a))

[False False  True  True  True  True]

#1.	Write a Pandas program to add, subtract, multiple and divide two Pandas Series. 
#Sample Series: [2, 4, 6, 8, 10], [1, 3, 5, 7, 9]
import pandas as pd
d1 = pd.Series([2, 4, 6, 8, 10])
d2 = pd.Series([1, 3, 5, 7, 9])
ds = d1 + d2
print("Add two Panda Series:")
print(ds)
print("Subtract two Panda Series:")
ds = d1 - d2
print(ds)
print("Multiply two Panda Series:")
ds = d1 * d2
print(ds)
print("Divide two Panda Series:")
ds = d1 / d2
print(ds)

Add two Panda Series:
0     3
1     7
2    11
3    15
4    19
dtype: int64
Subtract two Panda Series:
0    1
1    1
2    1
3    1
4    1
dtype: int64
Multiply two Panda Series:
0     2
1    12
2    30
3    56
4    90
dtype: int64
Divide two Panda Series:
0    2.000000
1    1.333333
2    1.200000
3    1.142857
4    1.111111
dtype: float64

#2.	Write a Pandas program to compare the elements of the two Pandas Series. 
#Sample Series: [2, 4, 6, 8, 10], [1, 3, 5, 7, 10]
import pandas as pd
s1 = pd.Series([2, 4, 6, 8, 10])
s2 = pd.Series([1, 3, 5, 7, 10])
print("Compare the elements of two Series:")
print("Equals:")
print(s1 == s2)

Compare the elements of two Series:
Equals:
0    False
1    False
2    False
3    False
4     True
dtype: bool

#Write a Pandas program to change the data type of given a column or a Series.  
import pandas as pd
s1 = pd.Series(['11', '22', 'swift', '30.82', '33'])
print(s1)
print("Change the data type to numeric:")
s2 = pd.to_numeric(s1, errors='coerce')
print(s2) 

0       11
1       22
2    swift
3    30.82
4       33
dtype: object
Change the data type to numeric:
0    11.00
1    22.00
2      NaN
3    30.82
4    33.00
dtype: float64

#Write a Pandas program to convert a given Series to an array.  
import pandas as pd
import numpy as np
s1 = pd.Series(['17', '15', '52', '18.21', 'Paris'])
print(s1)
print("Converting to an array")
a = np.array(s1.values.tolist())
print (a)

0       17
1       15
2       52
3    18.21
4    Paris
dtype: object
Converting to an array
['17' '15' '52' '18.21' 'Paris']

#Write a Pandas program to sort a given Series.   
import pandas as pd
p = pd.Series(['Paris', '21', 'Tokyo', '27.21', '41'])
print(p)
new_p = pd.Series(p).sort_values()
print(new_p)

0    Paris
1       21
2    Tokyo
3    27.21
4       41
dtype: object
1       21
3    27.21
4       41
0    Paris
2    Tokyo
dtype: object

#Write a Pandas program to create the mean and standard deviation of the data of a given Series. 
import pandas as pd
s = pd.Series(data = [1,2,3,4,5,6])
print(s)
print("Mean:",s.mean())
print("Standard deviation:",s.std())

0    1
1    2
2    3
3    4
4    5
5    6
dtype: int64
Mean: 3.5
Standard deviation: 1.8708286933869707

#Write a Pandas program to get the items of a given series not present in another given series. 
import pandas as pd
sr1 = pd.Series([7, 2, 10, 4, 5])
sr2 = pd.Series([2, 4, 6, 8, 10])
print("\nItems of sr1 not present in sr2:")
result = sr1[~sr1.isin(sr2)]
print(result)

Items of sr1 not present in sr2:
0    7
4    5
dtype: int64

#Write a Pandas program to get the items which are not common of two given series. 
import pandas as pd
import numpy as np
sr1 = pd.Series([1, 2, 3, 4, 5])
sr2 = pd.Series([2, 4, 6, 8, 10])
print("\nItems of a given series not present in another given series:")
sr11 = pd.Series(np.union1d(sr1, sr2))
sr22 = pd.Series(np.intersect1d(sr1, sr2))
result = sr11[~sr11.isin(sr22)]
print(result)

Items of a given series not present in another given series:
0     1
2     3
4     5
5     6
6     8
7    10
dtype: int64

#Write a Pandas program to compute the minimum, 25th percentile, median, 75th, and maximum of a given series.
import pandas as pd
import numpy as np
num_state = np.random.RandomState(50)
num_series = pd.Series(num_state.normal(10, 4, 20))
print("Original Series:")
print(num_series)
result = np.percentile(num_series, q=[0, 25, 50, 75, 100])
print("\nMinimum, 25th percentile, median, 75th, and maximum of a given series:")
print(result)

Original Series:
0      3.758592
1      9.876090
2      7.516286
3      4.141678
4     15.647784
5      8.093071
6      6.878123
7     14.281071
8      4.870830
9      4.690084
10    10.505351
11    13.448775
12    12.786948
13     8.661739
14     6.009896
15    16.395633
16    23.256301
17    13.951082
18    10.495465
19    12.971142
dtype: float64

Minimum, 25th percentile, median, 75th, and maximum of a given series:
[ 3.75859157  6.66106629 10.18577731 13.57435161 23.25630138]

#Write a Pandas program to display most frequent value in a given series and replace everything else as 'Other' in the series.
import pandas as pd
import numpy as np
np.random.RandomState(100)
num_series = pd.Series(np.random.randint(1, 5, [15]))
print("Original Series:")
print(num_series)
print("Top 2 Freq:", num_series.value_counts())
result = num_series[~num_series.isin(num_series.value_counts().index[:1])] = 'Other'
print(num_series)

Original Series:
0     2
1     2
2     1
3     4
4     2
5     2
6     3
7     1
8     1
9     3
10    3
11    4
12    1
13    1
14    4
dtype: int32
Top 2 Freq: 1    5
2    4
4    3
3    3
dtype: int64
0     Other
1     Other
2         1
3     Other
4     Other
5     Other
6     Other
7         1
8         1
9     Other
10    Other
11    Other
12        1
13        1
14    Other
dtype: object

#Write a Pandas program to extract items at given positions of a given series. 
import pandas as pd
num_series = pd.Series(list('2390238923902390239023'))
element_pos = [0, 2, 6, 11, 21]
result = num_series.take(element_pos)
print("\nExtract items at given positions of the said series:")
print(result)

Extract items at given positions of the said series:
0     2
2     9
6     8
11    0
21    3
dtype: object

#Write a Pandas program convert the first and last character of each word to upper case in each word of a given series. 
import pandas as pd
s = pd.Series(['london', 'mumbai', 'paris', 'madrid'])
result = s.map(lambda x: x[0].upper() + x[1:-1] + x[-1].upper())
print("First and last character of each word to upper case:")
print(result)

First and last character of each word to upper case:
0    LondoN
1    MumbaI
2     PariS
3    MadriD
dtype: object

#Write a Pandas program to convert a series of date strings to a timeseries. 
import pandas as pd
date_series = pd.Series(['02 Apr 2011', '22-06-2018', '20200307', '2021/05/06', '2010-04-12', '2019-04-06T11:20'])
print("Date strings to a timeseries:")
print(pd.to_datetime(date_series))

Date strings to a timeseries:
0   2011-04-02 00:00:00
1   2018-06-22 00:00:00
2   2020-03-07 00:00:00
3   2021-05-06 00:00:00
4   2010-04-12 00:00:00
5   2019-04-06 11:20:00
dtype: datetime64[ns]

import pandas as pd
from dateutil.parser import parse
date_series = pd.Series(['01 Jan 2015', '10-02-2016', '20180307', '2014/05/06', '2016-04-12', '2019-04-06T11:20'])
print("Original Series:")
print(date_series)
date_series = date_series.map(lambda x: parse(x))
print("Day of month:")
print(date_series.dt.day.tolist())
print("Day of year:")
print(date_series.dt.dayofyear.tolist())
print("Week number:")
print(date_series.dt.weekofyear.tolist())
print("Day of week:")
print(date_series.dt.isocalendar().week.tolist())

Original Series:
0         01 Jan 2015
1          10-02-2016
2            20180307
3          2014/05/06
4          2016-04-12
5    2019-04-06T11:20
dtype: object
Day of month:
[1, 2, 7, 6, 12, 6]
Day of year:
[1, 276, 66, 126, 103, 96]
Week number:
[1, 39, 10, 19, 15, 14]
Day of week:
[1, 39, 10, 19, 15, 14]

C:\Users\deepdesk\AppData\Local\Temp/ipykernel_6104/1185217349.py:12: FutureWarning: Series.dt.weekofyear and Series.dt.week have been deprecated.  Please use Series.dt.isocalendar().week instead.
  print(date_series.dt.weekofyear.tolist())

#Write a Pandas program to calculate the number of characters in each word in a given series.
import pandas as pd
series1 = pd.Series(['tokyo', 'mumbai', 'paris', 'rome'])
result = series1.map(lambda x: len(x))
print("Number of characters in each word in the said series:")
print(result)

Number of characters in each word in the said series:
0    5
1    6
2    5
3    4
dtype: int64

#Write a Pandas program to get the powers of an array values element-wise.  Note: First array elements raised to powers from second array
import pandas as pd
df = pd.DataFrame({'X':[78,85,96,80,86], 'Y':[84,94,89,83,86],'Z':[86,97,96,72,83]});
print(df)

    X   Y   Z
0  78  84  86
1  85  94  97
2  96  89  96
3  80  83  72
4  86  86  83

#Write a Pandas program to create and display a DataFrame from a specified dictionary data which has the index labels.
import pandas as pd
import numpy as np

exam_data  = {'Name': ['Ronaldo', 'Messi', 'Benzima', 'Pique', 'Ramos'],
        'Goals': [41, 40, 38, np.nan, 9,],
        'attempts': [55, 57, 56, 4, 20],
        'qualify': ['yes', 'yes', 'yes', 'no', 'no']}
labels = ['a', 'b', 'c', 'd', 'e']

df = pd.DataFrame(exam_data , index=labels)
print(df)

      Name  Goals  attempts qualify
a  Ronaldo   41.0        55     yes
b    Messi   40.0        57     yes
c  Benzima   38.0        56     yes
d    Pique    NaN         4      no
e    Ramos    9.0        20      no

#Write a Pandas program to display a summary of the basic information about a specified DataFrame and its data.
import pandas as pd
import numpy as np

exam_data  = {'Name': ['Ronaldo', 'Messi', 'Benzima', 'Pique', 'Ramos'],
        'Goals': [41, 40, 38, np.nan, 9,],
        'attempts': [55, 57, 56, 4, 20],
        'qualify': ['yes', 'yes', 'yes', 'no', 'no']}
labels = ['a', 'b', 'c', 'd', 'e']

df = pd.DataFrame(exam_data , index=labels)
print("Summary of the basic information about this DataFrame and its data:")
print(df.info())

Summary of the basic information about this DataFrame and its data:
<class 'pandas.core.frame.DataFrame'>
Index: 5 entries, a to e
Data columns (total 4 columns):
 #   Column    Non-Null Count  Dtype  
---  ------    --------------  -----  
 0   Name      5 non-null      object 
 1   Goals     4 non-null      float64
 2   attempts  5 non-null      int64  
 3   qualify   5 non-null      object 
dtypes: float64(1), int64(1), object(2)
memory usage: 200.0+ bytes
None

import pandas as pd
import numpy as np

exam_data  = {'Name': ['Ronaldo', 'Messi', 'Benzima', 'Pique', 'Ramos'],
        'Goals': [41, 40, 38, np.nan, 9,],
        'attempts': [55, 57, 56, 4, 20],
        'qualify': ['yes', 'yes', 'yes', 'no', 'no']}
labels = ['a', 'b', 'c', 'd', 'e']
df = pd.DataFrame(exam_data , index=labels)
print("First three rows of the data frame:")
print(df.iloc[:3])

First three rows of the data frame:
      Name  Goals  attempts qualify
a  Ronaldo   41.0        55     yes
b    Messi   40.0        57     yes
c  Benzima   38.0        56     yes

import pandas as pd
import numpy as np

exam_data  = {'Name': ['Ronaldo', 'Messi', 'Benzima', 'Pique', 'Ramos'],
        'Goals': [41, 40, 38, np.nan, 9,],
        'attempts': [55, 57, 56, 4, 20],
        'qualify': ['yes', 'yes', 'yes', 'no', 'no']}
labels = ['a', 'b', 'c', 'd', 'e']

df = pd.DataFrame(exam_data , index=labels)
print("Select specific columns and rows:")
print(df.iloc[[1, 3, 4,], [1, 3]])

Select specific columns and rows:
   Goals qualify
b   40.0     yes
d    NaN      no
e    9.0      no

#Write a Pandas program to count the number of rows and columns of a DataFrame.
import pandas as pd
import numpy as np

exam_data  = {'Name': ['Ronaldo', 'Messi', 'Benzima', 'Pique', 'Ramos'],
        'Goals': [41, 40, 38, np.nan, 9,],
        'attempts': [55, 57, 56, 4, 20],
        'qualify': ['yes', 'yes', 'yes', 'no', 'no']}
labels = ['a', 'b', 'c', 'd', 'e']

df = pd.DataFrame(exam_data , index=labels)
total_rows=len(df.axes[0])
total_cols=len(df.axes[1])
print("Number of Rows: "+str(total_rows))
print("Number of Columns: "+str(total_cols))

Number of Rows: 5
Number of Columns: 4

#Write a Pandas program to count the number of rows and columns of a DataFrame.
import pandas as pd
import numpy as np

exam_data  = {'Name': ['Ronaldo', 'Messi', 'Benzima', 'Pique', 'Ramos'],
        'Goals': [41, 40, 38, np.nan, 9,],
        'attempts': [55, 57, 56, 4, 20],
        'qualify': ['yes', 'yes', 'yes', 'no', 'no']}
labels = ['a', 'b', 'c', 'd', 'e']

df = pd.DataFrame(exam_data , index=labels)
total_rows=len(df.axes[0])
total_cols=len(df.axes[1])
print("Number of Rows: "+str(total_rows))
print("Number of Columns: "+str(total_cols))

Number of Rows: 5
Number of Columns: 4

#Write a Pandas program to select the rows where number of attempts in the examination is less than 2 and score greater than 15.  
#Sample Python dictionary data and list labels:
#exam_data = {'name': ['Anastasia', 'Dima', 'Katherine', 'James', 'Emily', 'Michael', 'Matthew', 'Laura', 'Kevin', 'Jonas'],
#'score': [12.5, 9, 16.5, np.nan, 9, 20, 14.5, np.nan, 8, 19],
#'attempts': [1, 3, 2, 3, 2, 3, 1, 1, 2, 1],
#'qualify': ['yes', 'no', 'yes', 'no', 'no', 'yes', 'yes', 'no', 'no', 'yes']}
#labels = ['a', 'b', 'c', 'd', 'e', 'f', 'g', labels = ['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j']
#Expected Output:
#Number of attempts in the examination is less than 2 and score greater than 15 :
#name score attempts qualify
#j Jonas 19.0 1 yes
import pandas as pd
import numpy as np
exam_data  = {'name': ['Anastasia', 'Dima', 'Katherine', 'James', 'Emily', 'Michael', 'Matthew', 'Laura', 'Kevin', 'Jonas'],
        'score': [12.5, 9, 16.5, np.nan, 9, 20, 14.5, np.nan, 8, 19],
        'attempts': [1, 3, 2, 3, 2, 3, 1, 1, 2, 1],
        'qualify': ['yes', 'no', 'yes', 'no', 'no', 'yes', 'yes', 'no', 'no', 'yes']}
labels = ['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j']
df = pd.DataFrame(exam_data , index=labels)
print("Number of attempts in the examination is less than 2 and score greater than 15 :")
print(df[(df['attempts'] < 2) & (df['score'] > 15)])

Number of attempts in the examination is less than 2 and score greater than 15 :
    name  score  attempts qualify
j  Jonas   19.0         1     yes

#Write a Pandas program to calculate the sum of the examination attempts by the students. (refer previous question 8’s sample data)
import pandas as pd
import numpy as np
exam_data  = {'name': ['Anastasia', 'Dima', 'Katherine', 'James', 'Emily', 'Michael', 'Matthew', 'Laura', 'Kevin', 'Jonas'],
        'score': [12.5, 9, 16.5, np.nan, 9, 20, 14.5, np.nan, 8, 19],
        'attempts': [1, 3, 2, 3, 2, 3, 1, 1, 2, 1],
        'qualify': ['yes', 'no', 'yes', 'no', 'no', 'yes', 'yes', 'no', 'no', 'yes']}
labels = ['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j']

df = pd.DataFrame(exam_data , index=labels)
print("\nSum of the examination attempts by the students:")
print(df['attempts'].sum())

Sum of the examination attempts by the students:
19

#Write a Pandas program to calculate the mean score for each different student in DataFrame. (refer previous question 8’s sample data)
import pandas as pd
import numpy as np
exam_data  = {'name': ['Anastasia', 'Dima', 'Katherine', 'James', 'Emily', 'Michael', 'Matthew', 'Laura', 'Kevin', 'Jonas'],
        'score': [12.5, 9, 16.5, np.nan, 9, 20, 14.5, np.nan, 8, 19],
        'attempts': [1, 3, 2, 3, 2, 3, 1, 1, 2, 1],
        'qualify': ['yes', 'no', 'yes', 'no', 'no', 'yes', 'yes', 'no', 'no', 'yes']}
labels = ['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j']

df = pd.DataFrame(exam_data , index=labels)
print("\nMean score for each different student in data frame:")
print(df['score'].mean())

Mean score for each different student in data frame:
13.5625

#Write a Pandas program to append a new row 'k' to data frame with given values for each column. Now delete the new row and return the original DataFrame. (refer previous question 8’s sample data)
import pandas as pd
import numpy as np
exam_data  = {'name': ['Anastasia', 'Dima', 'Katherine', 'James', 'Emily', 'Michael', 'Matthew', 'Laura', 'Kevin', 'Jonas'],
        'score': [12.5, 9, 16.5, np.nan, 9, 20, 14.5, np.nan, 8, 19],
        'attempts': [1, 3, 2, 3, 2, 3, 1, 1, 2, 1],
        'qualify': ['yes', 'no', 'yes', 'no', 'no', 'yes', 'yes', 'no', 'no', 'yes']}
labels = ['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j']
df = pd.DataFrame(exam_data , index=labels)
print("Original rows:")
print(df)
print("\nAppend a new row:")
df.loc['k'] = [1, 'Suresh', 'yes', 15.5]
print("Print all records after insert a new record:")
print(df)
print("\nDelete the new row and display the original  rows:")
df = df.drop('k')
print(df)

Original rows:
        name  score  attempts qualify
a  Anastasia   12.5         1     yes
b       Dima    9.0         3      no
c  Katherine   16.5         2     yes
d      James    NaN         3      no
e      Emily    9.0         2      no
f    Michael   20.0         3     yes
g    Matthew   14.5         1     yes
h      Laura    NaN         1      no
i      Kevin    8.0         2      no
j      Jonas   19.0         1     yes

Append a new row:
Print all records after insert a new record:
        name   score attempts qualify
a  Anastasia    12.5        1     yes
b       Dima     9.0        3      no
c  Katherine    16.5        2     yes
d      James     NaN        3      no
e      Emily     9.0        2      no
f    Michael    20.0        3     yes
g    Matthew    14.5        1     yes
h      Laura     NaN        1      no
i      Kevin     8.0        2      no
j      Jonas    19.0        1     yes
k          1  Suresh      yes    15.5

Delete the new row and display the original  rows:
        name score attempts qualify
a  Anastasia  12.5        1     yes
b       Dima   9.0        3      no
c  Katherine  16.5        2     yes
d      James   NaN        3      no
e      Emily   9.0        2      no
f    Michael  20.0        3     yes
g    Matthew  14.5        1     yes
h      Laura   NaN        1      no
i      Kevin   8.0        2      no
j      Jonas  19.0        1     yes

#Write a Pandas program to sort the DataFrame first by 'name' in descending order, then by 'score' in ascending order. (refer previous question 8’s sample data)
import pandas as pd
import numpy as np
exam_data  = {'name': ['Anastasia', 'Dima', 'Katherine', 'James', 'Emily', 'Michael', 'Matthew', 'Laura', 'Kevin', 'Jonas'],
        'score': [12.5, 9, 16.5, np.nan, 9, 20, 14.5, np.nan, 8, 19],
        'attempts': [1, 3, 2, 3, 2, 3, 1, 1, 2, 1],
        'qualify': ['yes', 'no', 'yes', 'no', 'no', 'yes', 'yes', 'no', 'no', 'yes']}
labels = ['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j']
df = pd.DataFrame(exam_data , index=labels)
df.sort_values(by=['name', 'score'], ascending=[False, True])
print(df)

        name  score  attempts qualify
a  Anastasia   12.5         1     yes
b       Dima    9.0         3      no
c  Katherine   16.5         2     yes
d      James    NaN         3      no
e      Emily    9.0         2      no
f    Michael   20.0         3     yes
g    Matthew   14.5         1     yes
h      Laura    NaN         1      no
i      Kevin    8.0         2      no
j      Jonas   19.0         1     yes

#Write a Pandas program to replace the 'qualify' column contains the values 'yes' and 'no' with True and False. (refer previous question 8’s sample data)
import pandas as pd
import numpy as np
exam_data  = {'name': ['Anastasia', 'Dima', 'Katherine', 'James', 'Emily', 'Michael', 'Matthew', 'Laura', 'Kevin', 'Jonas'],
        'score': [12.5, 9, 16.5, np.nan, 9, 20, 14.5, np.nan, 8, 19],
        'attempts': [1, 3, 2, 3, 2, 3, 1, 1, 2, 1],
        'qualify': ['yes', 'no', 'yes', 'no', 'no', 'yes', 'yes', 'no', 'no', 'yes']}
labels = ['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j']
df = pd.DataFrame(exam_data , index=labels)
print("Replace the 'qualify' column contains the values 'yes' and 'no'  with True and  False:")
df['qualify'] = df['qualify'].map({'yes': True, 'no': False})
print(df)

Replace the 'qualify' column contains the values 'yes' and 'no'  with True and  False:
        name  score  attempts  qualify
a  Anastasia   12.5         1     True
b       Dima    9.0         3    False
c  Katherine   16.5         2     True
d      James    NaN         3    False
e      Emily    9.0         2    False
f    Michael   20.0         3     True
g    Matthew   14.5         1     True
h      Laura    NaN         1    False
i      Kevin    8.0         2    False
j      Jonas   19.0         1     True

#Write a Pandas program to change the name 'James' to 'Suresh' in name column of the DataFrame. (refer previous question 8’s sample data)
import pandas as pd
import numpy as np
exam_data  = {'name': ['Anastasia', 'Dima', 'Katherine', 'James', 'Emily', 'Michael', 'Matthew', 'Laura', 'Kevin', 'Jonas'],
        'score': [12.5, 9, 16.5, np.nan, 9, 20, 14.5, np.nan, 8, 19],
        'attempts': [1, 3, 2, 3, 2, 3, 1, 1, 2, 1],
        'qualify': ['yes', 'no', 'yes', 'no', 'no', 'yes', 'yes', 'no', 'no', 'yes']}
labels = ['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j']
df = pd.DataFrame(exam_data , index=labels)
print("Change the name 'James' to ‘Suresh’:")
df['name'] = df['name'].replace('James', 'Suresh')
print(df)

Change the name 'James' to ‘Suresh’:
        name  score  attempts qualify
a  Anastasia   12.5         1     yes
b       Dima    9.0         3      no
c  Katherine   16.5         2     yes
d     Suresh    NaN         3      no
e      Emily    9.0         2      no
f    Michael   20.0         3     yes
g    Matthew   14.5         1     yes
h      Laura    NaN         1      no
i      Kevin    8.0         2      no
j      Jonas   19.0         1     yes

#Write a Pandas program to iterate over rows in a DataFrame.
import pandas as pd
import numpy as np
exam_data = [{'name':'tim', 'score':12.5}, {'name':'joe','score':9}, {'name':'rachel','score':16.5}]
df = pd.DataFrame(exam_data)
for index, row in df.iterrows():
    print(row['name'], row['score'])

tim 12.5
joe 9.0
rachel 16.5

import pandas as pd
import numpy as np
d = {'name': ['Ronaldo','Messi','Benzima'], 'c_clubs': ['Manchester United','PSG','Real Madrid'], 'p_clubs': ['Juventus','Barcelona','N/A']}
df = pd.DataFrame(data=d)
print('After add one row:')
df2 = {'name':'Ramos', 'c_clubs':'PSG', 'p_clubs':'Real Madrid'}
df = df.append(df2, ignore_index=True)
print(df)

After add one row:
      name            c_clubs      p_clubs
0  Ronaldo  Manchester United     Juventus
1    Messi                PSG    Barcelona
2  Benzima        Real Madrid          N/A
3    Ramos                PSG  Real Madrid

import pandas as pd
import numpy as np
d = {'name': ['Ronaldo','Messi','Benzima'], 'c_clubs': ['Manchester United','PSG','Real Madrid'], 'p_clubs': ['Juventus','Barcelona','N/A']}
df = pd.DataFrame(data=d)
print('After altering name and p_clubs')
df = df[['p_clubs', 'c_clubs', 'name']]
print(df)

After altering name and p_clubs
     p_clubs            c_clubs     name
0   Juventus  Manchester United  Ronaldo
1  Barcelona                PSG    Messi
2        N/A        Real Madrid  Benzima

#Write a Pandas program to select rows from a given DataFrame based on values in some columns.
import pandas as pd
import numpy as np
d = {'name': ['Ronaldo','Messi','Benzima'], 'c_clubs': ['Manchester United','PSG','Real Madrid'], 'p_clubs': ['Juventus','Barcelona','N/A']}
df = pd.DataFrame(data=d)
print('Rows for name value == Messi')
print(df.loc[df['name'] == 'Messi'])

Rows for name value == Messi
    name c_clubs    p_clubs
1  Messi     PSG  Barcelona

#Write a Pandas program to rename columns of a given DataFrame
import pandas as pd
import numpy as np
d = {'name': ['Ronaldo','Messi','Benzima'], 'c_clubs': ['Manchester United','PSG','Real Madrid'], 'p_clubs': ['Juventus','Barcelona','N/A']}
df = pd.DataFrame(data=d)
df.columns = ['Column1', 'Column2', 'Column3']
df = df.rename(columns={'name': 'Column1', 'c_clubs': 'Column2', 'p_clubs': 'Column3'})
print(df)

   Column1            Column2    Column3
0  Ronaldo  Manchester United   Juventus
1    Messi                PSG  Barcelona
2  Benzima        Real Madrid        N/A

#Write a Pandas program to get list from DataFrame column headers.
import pandas as pd
import numpy as np
d = {'name': ['Ronaldo','Messi','Benzima'], 'c_clubs': ['Manchester United','PSG','Real Madrid'], 'p_clubs': ['Juventus','Barcelona','N/A']}
df = pd.DataFrame(data=d)
print(list(df.columns.values))

['name', 'c_clubs', 'p_clubs']